Affiliation:
1. MARMARA ÜNİVERSİTESİ, FEN BİLİMLERİ ENSTİTÜSÜ
2. MARMARA ÜNİVERSİTESİ, TEKNOLOJİ FAKÜLTESİ, BİLGİSAYAR MÜHENDİSLİĞİ BÖLÜMÜ
Abstract
Alzheimer's Disease (AD) is a type of dementia, also called cognitive impairment. In cases where measures are not taken against the disease, it may result in a decrease in the quality of life of the person and result in very serious consequences. While it presents with neurological consequences such as decreased functions of thinking and memory, it may result in death in advanced cases. The fact that the treatment is not completely possible makes the place of early diagnosis and intervention important for AD. As a result of the researches carried out in the study, it was seen that there are many studies and scientific content within the framework of AD. A method for early diagnosis of the disease was evaluated by using an open source shared dataset, which includes some disease-specific values and demographic characteristics. By using Artificial Neural Networks (ANN) model, which is one of the machine learning methods, it is aimed to be useful for other studies to take precautions for early detection of the disease. With the ANN, which was classified as dementia and non-dementia individuals, Root Mean Square Error (RMSE) value 0.2302, Mean Absolute Error (MAE) value 0.1899 and accuracy rate of 98.5% was obtained.
Publisher
Muhendislik Bilimleri ve Tasarim Dergisi
Subject
Colloid and Surface Chemistry,Physical and Theoretical Chemistry
Reference25 articles.
1. Acharya, S. 2021. What are RMSE and MAE?. https://towardsdatascience.com/what-are-rmse-and-mae-e405ce230383 (Access Date: 22.08.2023).
2. Aljović, A., Badnjević, A., Gurbeta, L. 2016. Artificial neural networks in the discrimination of Alzheimer's disease using biomarkers data. In 2016 5th Mediterranean Conference on Embedded Computing (MECO), 12-16 June, Bar, 286-289.
3. Buyrukoğlu, S. 2021. Early Detection of Alzheimer’s Disease Using Data Mining: Comparison of Ensemble Feature Selection Approaches. Konya Mühendislik Bilimleri Dergisi, 9(1), 50-61.
4. Chai, T., Draxler, R. R. 2014. Root mean square error (RMSE) or mean absolute error (MAE)?–Arguments against avoiding RMSE in the literature. Geoscientific model development, 7(3), 1247-1250.
5. Delikanlı Akbay, G. 2019. Alzheimer Hastalığında B12 Vitamini Eksikliği. Cumhuriyet Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi, 4(3), 22-28.